S.I. : THE H2020 EUROPEAN PROJECT LIQUEFACT
A computational platform to assess liquefaction‑induced loss at critical infrastructures scale
A. Meslem1 · H. Iversen2 · K. Iranpour3 · D. Lang4
Received: 5 April 2020 / Accepted: 10 December 2020
© The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature 2021
Abstract
In the framework of the multi-disciplinary LIQUEFACT project, funded under the Euro- pean Commission’s Horizon 2020 program, the LIQUEFACT Reference Guide software has been developed, incorporating both data and methodologies collected and elaborated in the project’s various work packages. Specifically, this refers to liquefaction hazard maps, methodologies and results of liquefaction vulnerability analysis for both building typolo- gies and critical infrastructures, liquefaction mitigation measures as well as cost-benefit considerations. The software is targeting a wider range of user groups with different levels of technical background as well as requirements (urban planners, facility managers, struc- tural and geotechnical engineers, or risk modelers). In doing so, the LIQUEFACT soft- ware shall allow the user assessing the liquefaction-related risk as well as assisting them in liquefaction mitigation planning. Dependent on the user’s requirements, the LIQUEFACT software can be used to separately conduct the liquefaction hazard analysis, the risk anal- ysis, and the mitigation analysis. At the stage of liquefaction hazard, the users can geo- locate their assets (buildings or infrastructures) against the pre-defined macrozonation and microzonation maps in the software and identify those assets/sites that are potentially sus- ceptible to an earthquake-induced liquefaction damage hazard. For potentially susceptible sites the user is able to commission a detailed ground investigation (e.g. CPT, SPT or VS30 profile) and this data can be used by the software to customise the level of susceptibility to specific site conditions. The users can either use inbuilt earthquake scenarios or enter their own earthquake scenario data. In the Risk Analysis, the user can estimate the level of impact of the potential liquefaction threat on the asset and evaluate the performance. For the Mitigation Analysis, the user can develop a customized mitigation framework based on the outcome of the risk and cost-benefit analysis.
Keywords Liquefaction hazard · Liquefaction risk · Cost-benefit based mitigation planning · Software toolbox
* A. Meslem
1 Department of Earthquake Hazard and Risk, NORSAR, Kjeller, Norway
2 Department of Solutions, NORSAR, Kjeller, Norway
3 Department of Microseismic Monitoring, NORSAR, Kjeller, Norway
4 Department of Natural Hazards, Norwegian Geotechnical Institute, Oslo, Norway
1 Introduction
Over the past years, several seismic hazard and risk analysis programmes and software tools have been introduced and widely used for design and assessment purposes. The com- parative investigation that was carried-out in the framework of the LIQUEFACT project (funded under the European Commission’s Horizon 2020 framework program) for existing programmes and software tools, focusing in particular on earthquake-induced liquefaction, has revealed that, in general, most of these programmes and software tools only allow the user to compute the liquefaction potential and vertical settlement along a vertical soil pro- file knowing the results of a CPT, CPTU, SPT or Vs30 test, and they do not provide fea- tures allowing the conduct of liquefaction microzonation mapping; e.g. LiquefyPro (Civ- ilTech 2015), LiqIT (GeoLogismiki 2006) which has recently been replaced by LiqSVs (GeoLogismiki 2020), NovoLIQ (NovoTech 2020). Few software, e.g. CLiq (GeoLogis- miki 2018), do allow the user to visualize the spatial variation of liquefaction hazard across a site. However, they do not provide the possibility to also assess the impact of liquefaction to structures and infrastructure facilities. In terms of user interface, software development format (compiled, source code), format of output, and proprietary software requirement, the current software tools can be categorized into 3 groups: Group-1 where programmes and software are distributed as source-code tools available as open-source with or with- out license or registration requirement. This group of programmes and software tools are mostly used for research purpose and require highly skilled users. The input and output data handling can be complicated and a time-consuming process. This can ultimately result in a very low number of users that can test the software, provide feedback, and contribute to improving the software. Group-2, where programmes and software tools are distributed as compiled tools available as open-source with or without license or registration require- ment. This group of programmes and software tools are also used for research purpose and some of them require highly skilled users. And Group-3: where the programmes and software tools are distributed as compiled tools with a user-friendly graphical interface.
Programmes from this group are distributed with commercial license, e.g. NovoLIQ by NovoTech (2020), CLiq by GeoLogismiki (2018).
One of the main objectives of the LIQUEFACT project is to bring civil engineers and relevant stakeholders all together in one easy-to-use platform where the users with different backgrounds can easily conduct different levels of analysis through a robust graphical user interface (GUI), exchange information more efficiently in a user-friendly environment, and the analysis output can be understandable by non-technical users. This requires the incor- poration of different attributes and features that would allow the users not only in making earthquake-induced liquefaction hazard analysis, but also in assessing the impact (risk), feasibility and cost-benefit of applying certain liquefaction mitigation techniques for the given earthquake-induced liquefaction threat.
In response to these above challenges, the LIQUEFACT Reference Guide software has been developed as one of the key outputs from the LIQUEFACT project. The software is a toolbox for liquefaction mitigation planning and decision support, able to estimate and predict the likely consequences of an Earthquake-Induced Liquefaction Disaster (EILD) to the most vulnerable regions of Europe. The development of the LIQUEFACT software involved the incorporation of data and state-of-the-art methodologies. Specifically, this refers to liquefac- tion susceptibility level maps (Lai et al. 2019a, b, 2020a, b; Meslem et al. 2019a, d), meth- odologies and results of liquefaction vulnerability analysis for both building typologies and critical infrastructures (Viana da Fonseca et al. 2018a, b; Millen et al 2018, 2019a, b; Meslem
et al. 2019b, d), liquefaction mitigation measures as well as cost-benefit considerations (Jones et al. 2019, 2020; Meslem et al. 2019c, d). The development process of the LIQUEFACT soft- ware has also benefited from the comparative investigation that was carried out for the existing earthquake-induced liquefaction analysis programmes and software, and helped in developing ideas regarding the attributes that the LIQUEFACT software should feature, and implement most appropriate design strategy.
As mentioned earlier, the LIQUEFACT software is targeting a wider range of user groups with different levels of technical background as well as requirements (urban planners, facility managers, structural and geotechnical engineers, or risk modelers). In doing so, the LIQUE- FACT software shall allow the user making informed assessments on the feasibility and cost- benefit of applying certain liquefaction mitigation techniques for a given earthquake-induced liquefaction threat. Dependent on the user’s requirements, the LIQUEFACT software can be used to separately conduct the liquefaction hazard analysis, the risk analysis, and the mitiga- tion analysis. At the stage of liquefaction hazard analysis, the user can conduct two stages of liquefaction susceptibility level analysis, qualitative or quantitative assessment, depending on how detailed the available input data are and type of result the user want to obtain. In Risk analysis, the user can estimate level of impact of the potential liquefaction threat on the asset and evaluate the performance in terms of physical capacity, content and business activity. For the Mitigation Analysis, the user can develop a customized mitigation framework based on the outcome of risk and cost-benefit analysis.
The LIQUEFACT software was designed and developed as an easy-to-use software tool- box, where all the different analysis processes are handled through a robust GUI providing a user-friendly environment for preparing the input information for the LIQUEFACT software and work on the database. Having data handled through a user-friendly graphical interface can increase the number of users that can test the software, hence, helping in the future develop- ment and improvement of the software based on the users’ feedback. The software also uses Geographic Information Systems (GIS) technology, allowing the user to visualize the spatial relationships between various geographic assets or resources for the specific hazard being modelled, a crucial function in the planning process. The LIQUEFACT software development was also based on various detailed feedbacks on both the engineering science and practical usefulness of each feature incorporated in the tool. The development has also been validated during workshops (International Expert Advisory Panel review workshops, several workshops with urban planners, facility managers, structural and geotechnical engineers, or risk model- ers) and tested at various sites (published by different project’s partners) during the LIQUE- FACT project lifetime (Modoni et al. 2019a, 2019b; Paolella et al. 2019, 2020; Jones et al.
2020; Oztoprak et al. 2019; Quintero et al. 2019).
This paper provides insights on the concept and the philosophy of analysis process that characterize the LIQUEFACT software, illustrating and describing how the various methodol- ogies and different forms of data, provided by the other work packages, have been integrated, and illustrates the interaction between the various protocols and modules of the hazard, risk and mitigation analysis.
2 Main concept of the liquefact software
Earthquake-induced liquefaction damage assessment is a multi-process analysis that requires different types and forms of input data related to geology and seismology of the site, geotechnical data, and structure-foundation system characteristics of the asset under
risk. To this end, the LIQUEFACT software has been designed in a way that earthquake- induced liquefaction damage (EILD) assessment is conducted at three independent proto- cols of analysis to provide more flexibility to the user’s requirements with respect to the level of analysis to be implemented and type of input data that are available.
The three-independent protocols of analysis implemented in the software are related to:
liquefaction hazard and susceptibility assessment, risk assessment, and development and implementation of mitigation framework (see Fig. 1). At the stage of the liquefaction haz- ard assessment, assets under investigation (buildings or infrastructures) can be geo-located against pre-defined macrozonation and microzonation maps in the software and identify those assets/sites that are potentially susceptible to an EILD hazard. For potentially suscep- tible sites a detailed ground investigation (e.g. CPT, SPT or VS30 profile) could be commis- sioned and used by the software to customise the level of susceptibility to specific site con- ditions. The ground shaking distribution can be defined either by using inbuilt earthquake scenarios or by providing (user-supplied) earthquake scenario data. In Risk assessment, the level of impact of the potential liquefaction threat on the asset/assets can be estimated and the performance can be evaluated. For the Mitigation Analysis, a customized mitiga- tion framework can be developed based on the outcome of risk and cost-benefit analysis combined with pre-defined applicability criteria and result of score rating for the various mitigation technologies.
These different analysis processes are handled through a robust GUI providing a user- friendly environment for preparing the input information for the LIQUEFACT software and work on the database (Fig. 2). The LIQUEFACT software is a C ++ based programme (Eng 2018) uses GIS technology, allowing the user to visualize the spatial relationships between various geographic assets or resources for the specific hazard being modelled, a crucial function in the planning process. Open Street Map (Bennet 2010) has been embed- ded in the LIQUEFACT mapping module, where individual buildings and street names can be viewed, and allowing the overlay of input data, e.g. data on buildings, liquefaction
Fig. 1 The LIQUEFACT software flow diagram
profiles, and ground shaking maps. Import of data into the LIQUEFACT software is based on tab-separated CSV files, unformatted TXT files or SHAPE files (ESRI defined formats) that will be converted to SQLite database files in the project. Results can be exported as SHAPE or CSV. SHAPE files can be exported as points or polygons. The database and result files in various formats are stored in a project directory.
3 Liquefaction susceptibility level assessment
Liquefaction susceptibility can be conducted at two levels of analysis depending on how detailed the available input data are and type of result that need to be obtained. The first level of assessment is based on the Qualitative approach where no detailed geotechnical soil profile data or specific information on the earthquake are required. The outcomes from this level of assessment can be used by asset managers and other stakeholders as guidance for a more detailed analysis (quantitative assessment). The second level of assessment is based on the Quantitative approach where detailed geotechnical soil profile and earthquake data are required (Meslem et al. 2019c, d).
3.1 Qualitative analysis of liquefaction hazard
The LIQUEFACT software incorporates the Qualitative approach-based liquefaction haz- ard assessment procedure, providing the possibility to identify whether an asset (e.g. indi- vidual building/critical infrastructure asset, portfolio of buildings/distributed infrastructure assets, etc.) is located in a geographical area likely to be affected by an EILD event. The level of exposures that the asset(s) is/are likely to be susceptible to is evaluated using quali- tative labels ranging such as “Non-Susceptible”, “No Liquefaction” to “Very High Risk of Liquefaction”, depending on the type of the liquefaction severity indicator used (see Table 1).
Fig. 2 The LIQUEFACT graphical user interface
The concept of the qualitative approach incorporated in the LIQUEFACT software is based on using pre-computed liquefaction hazard maps with qualitative classification labels representing levels of susceptibility which could be in terms of Liquefaction Susceptibility, Liquefaction Severity Number (LSN), Liquefaction Potential Index (LPI), or Probability of Liquefaction (PL). These are the most widespread indicators to evaluate the damage to the ground (Iwasaki et al. 1978; Tonkin and Taylor 2013; Van Ballegooy et al. 2014). Figure 3 shows some examples on how LIQUEFACT software is producing qualitative assessment of liquefaction risk potential based on the user-supplied qualitative maps.
Two options can be used to define the pre-computed liquefaction hazard maps: User- supplied where maps could be a result of local, regional or national level hazard assess- ment; or the option of pre-defined maps embedded in the LIQUEFACT software and which represents the macrozonation of liquefaction risk of the European territory which was addressed in the LIQUEFACT project (Lai et al. 2019b). These European earthquake- induced soil liquefaction risk maps were built using available datasets at a continental scale on the expected seismic hazard and on the geological, geomorphological, hydrogeological, shallow lithology and digital terrain information. The macrozonation maps were generated for different levels of severity of expected ground shaking from SHARE project (Grünthal and Wahlstrom 2013), characterized by a return period of 475, 975 and 2475 years, respec- tively (Fig. 4). Note that the use of European macrozonation maps is recommended only if the user wants to conduct liquefaction risk analysis at continental or large region-scale Table 1 Liquefaction hazard severity indicators and labels for qualitative classification
Liquefaction Hazard
(Susceptibility) Non-
Susceptible No Liquefaction Liquefaction Severity Number
(LSN) Low Liquefaction Risk Moderate Liquefaction
Risk High Liquefaction Risk Very High Liquefaction Risk
Liquefaction Potential Index
(LPI) Low Liquefaction Risk Moderate Liquefaction
Risk High Liquefaction Risk Very High Liquefaction Risk
Probability of Liquefaction
(PL) Low Liquefaction Risk Moderate Liquefaction
Risk High Liquefaction Risk Very High Liquefaction
Liquefaction Severity Indicator Liquefaction Susceptibility Qualitative Classification Labels Risk
Liquefaction
Non-Liquefaction Risk
Non-Liquefaction Risk
Non-Liquefaction Risk
Fig. 3 Examples of qualitative assessment of liquefaction risk potential in the LIQUEFACT software based on the user-supplied qualitative maps. a qualitative risk classification in terms of Liquefaction Susceptibil- ity. b qualitative risk classification in terms of Liquefaction Probability Index
level. The European macrozonation maps use three qualitative levels of hazard classifica- tion for range labels: Non-susceptible, No Liquefaction, and Liquefaction.
3.2 Quantitative analysis of liquefaction hazard
The concept of the quantitative approach consists of the number of analyses to be carried out in two main sequences, as illustrated in Fig. 5, and which are: Liquefaction Trigger- ing Analysis sequence to estimate the tendency of developing liquefaction under a given seismic input, and the analysis is based on computation of the factor of safety against liquefaction; and Liquefaction-induced Surficial Manifestations sequence to evaluate the effects at the ground level, where indicators are adopted to broadly quantify the severity of liquefaction.
3.2.1 Liquefaction triggering analysis
In the LIQUEFACT software, the triggering of liquefaction at a given site can be evalu- ated by applying the Cyclic Stress approach which requires full soil profile information as input data (Fig. 6). This approach implies the calculation of a liquefaction safety fac- tor (FSL) obtained by dividing the Cyclic Resistance Ratio (CRR) producing liquefaction with the Cyclic Stress Ratio (CSR) induced by the earthquake. According to this method, seismic liquefaction is triggered in a susceptible soil when the seismic demand (expressed as CSR) exceeds the resistance of such soils (expressed as CRR). The CRR is a representa- tion of the ability of the soil to resist the liquefaction demand and is related to its relative density and Fines Content (FC). It is also recognized that the stress conditions (confining
Fig. 4 The embedded European liquefaction prediction maps generated for different levels of severity of expected ground shaking, characterized by a return period of 475, 975 and 2475 years
pressure, cyclic shear and initial static shear stresses) play an important role in the liquefac- tion behaviour of soil, the type of failure mechanism and the mode of development of soil deformation, especially in the case of slopes of sandy deposits.
For the computation of liquefaction triggering, different methods can be used depending on type of soil profiles data: Cone Penetration Tests (CPT)-based soil profiles, Standard Fig. 5 Concept of liquefaction hazard assessment based on quantitative analysis
Fig. 6 The user-supplied soil profiles data in the LIQUEFACT software
Penetration Tests (SPT) or Vs-based soil profiles. For CPT and SPT data, the software incorporates the Boulanger and Idriss (2014, 2015, 2016) procedure to evaluate the Factor of Safety against liquefaction at each depth of a soil profile. For Vs-profile data, the evalua- tion of the Factor of Safety is based on the Andrus and Stokoe (2000) procedure.
Regarding the provision of seismic action, the LIQUEFACT software generates spatial distribution of ground motion in terms of peak ground acceleration (PGA) and spectral acceleration contour maps. This can be done either by conducting a deterministic scenario earthquake or by using already pre-computed ground motion distribution maps. (Fig. 7).
The deterministic scenario earthquake, which can be a repeat of any potential earthquake event (historic earthquake) or a hypothetical earthquake, can be carried-out in the software using a set of the earthquake source parameters. These parameters can be obtained from the available information related to geological, seismotectonic and geotechnical characteristics of the site of interest as well as physical modelling techniques to provide a reliable and robust deterministic basis for hazard and risk analysis. A scenario earthquake is defined by providing the location of the earthquake, focal depth, magnitude, fault orientation, and dip angle. Attenuation relationships (Ground Motion Prediction Equations—GMPE) are used to calculate ground shaking demand for rock site conditions. In general, they repre- sent response spectral acceleration ordinates, Sa (T), for 5% elastic damping.
For the option of pre-computed hazard maps, users can simply upload their own spa- tial ground motion distribution maps (that can be as an outcome of probabilistic or deter- ministic analysis), e.g. resulted from a specific local or regional seismic response analysis.
The use of the European SHARE probabilistic seismic hazard contour maps for Euro- Mediterranean region (Grünthal and Wahlstro 2013), and which has been embedded in the LIQUEFACT software to be used as basis to ground shaking, represents another alter- native for the pre-computed hazard maps option within the software. The SHARE maps were produced for different return periods: 73 years (50% in 50 years), 102 years (39%
in 50 years), 475 years (10% in 50 years), 975 years (5% in 50 years), 2475 years (2% in
Fig. 7 Provision of seismic ground motions in the LIQUEFACT software
50 years), 4975 years (1% in 50 years). The hazard values are referenced to a rock velocity of VS,30 = 800 m/s averaged over the uppermost 30 m. SHARE (reference) models earth- quakes as finite ruptures and includes all events with magnitudes MW ≥ 4.5 in the compu- tation of hazard values. SHARE introduces an innovative weighting scheme that reflects the importance of the input data sets considering their time horizon, thus emphasizing the geologic knowledge for products with longer time horizons and seismological data for shorter ones.
The values of ground shaking demand obtained from the different options described above are in general computed for rock condition, and then amplified by factors based on local soil conditions. This can be done using an average shear-wave velocity VS,30 value which is a user-supplied input data and the ground motion is amplified based on Eurocode 8 soil subclasses (CEN 2004), that have been embedded in the LIQUEFACT software, by assigning the soil type that agrees with the VS,30 value input data. Alternatively, the soil amplification factors provided by IBC-2006 (ICC 2006) and which are also associated to VS,30 values, can also be used.
For the definition of the shape for response spectrum, options are also provided between (a) the use of the Eurocode 8 code-design spectrum types (Type 1 in case that earthquakes with a surface-wave magnitude Ms > 5.5 are expected, and Type 2 for Ms ≤ 5.5); (b) the use of the full spectral acceleration from the pre-computed maps (i.e. user-supplied or SHARE maps); or (c) the use of spectral acceleration that can be resulted from a selected attenua- tion relationship if a deterministic scenario earthquake is conducted.
3.2.2 Liquefaction‑induced Surficial Manifestations
Once the Factor of Safety (FSL) has been calculated at each depth, synthetic indicators of the liquefaction severity on the ground (free field) can be evaluated. These integrate the contribution to the liquefaction of each layers, generally for the first 20 m of depth, giving a measure of the liquefaction severity on the surface (free field). In general terms, a lique- faction severity indicator can be defined as the integral of the product between a function of the Factor of Safety against Liquefaction f1(FSL) and a weight function that emphasizes the severity of liquefaction at a lower depth.
The LIQUEFACT software uses various liquefaction severity or damage potential indi- cators to provide a measure of the liquefaction-induced surficial evidence, based on the cumulative liquefaction response of a soil profile: Liquefaction Potential Index “LPI” (Iwa- saki et al. 1978); one-dimensional volumetric reconsolidation settlement Ground Defor- mation “GD” (Zhang et al. 2002); Liquefaction Severity Number “LSN” (Van Ballegooy et al. 2014). With these indicators the damage to the ground is quantified by integrating the estimated effects of liquefaction in the first 20 m depth (see Fig. 5).
In addition to these above well-known indicators, LIQUEFACT software also pro- duces liquefaction risk level in terms of Equivalent Soil Profile (ESP), a new hazard- independent liquefaction classification that was developed and addressed in LIQUE- FACT project (Millen et al. 2019a, b; Viana da Fonseca et al. 2018a). In the ESP soil profile is defined as an equivalent 3-layered soil profile. The classification consists of only three features, highly influential to the ground behaviour: the depth of the
INDEX=
∫
z max
f1(FSL) ∗w(z)dz
non-liquefying crust, and the thickness and liquefaction resistance of the potentially liquefiable layer. Figure 8 illustrates the general steps for the development of ESP and evaluation of the level of liquefaction hazard, as conducted in the LIQUEFACT soft- ware. The concept of this methodology consists of 2 main steps: Step 1 is about gener- ating 3-layered soil profile, i.e. the equivalent soil profile, from CPT, SPT or Vs data to evaluate the level of liquefaction hazard; Step 2 the methodology uses three govern- ing parameters: the depth of the crust (Dliq), the thickness of the liquefied layer (Hliq) and its liquefaction resistance (CRR n15). Typical ranges of values for each of these variables have been defined, from which 22 different soil profile classes (Table 2) were derived. Furthermore, the development of this process has also came up with a cor- respondence between ESP classes and LS values allowing the backward estimate of likely ESPs in a region given a liquefaction severity estimate. In fact, for the inves- tigated profiles, the LSN was computed for four different hazard levels representing:
low, moderate, high and severe seismicity (PGA values equal to 0.1 g, 0.2 g, 0.35 g, 0.5 g and Mw equal to 7.5). By applying the Bayes theorem, the conditional probabil- ity of finding each ESP class for a given LSN range was evaluated and plotted for the aforementioned four levels of seismicity. For more detailed information readers should refer to Viana da Fonseca et al. (2018a).
Figures 9 and 10 show examples of quantitative measures for liquefaction potential along with a qualitative assessment (Very Low to Very High) of the liquefaction risk level, as produced by the LIQUEFACT software. In the LIQUEFACT software, two types of interpolation techniques for mapping liquefaction risk levels are implemented: Geostatisti- cal Interpolation and Deterministic Interpolation procedures (Fig. 11). The implemented Geostatistical Interpolation is based on Kriging technique which utilizes the statistical properties of the measured points. Kriging techniques quantify the spatial autocorrela- tion among measured points and account for the spatial configuration of the sample points around the prediction location. The implemented Deterministic Interpolation is based on
Fig. 8 General steps of the development of equivalent soil profile (ESP) and range definition for classifica- tion (Millen et al. 2019a, b; Viana da Fonseca et al. 2018a)
Table 2 Concept and class of
equivalent soil profile (ESP) Soil resist- ance (CRR
liq)
Liquefiable layer (Hliq) Crust layer (Dliq) ESP profile
Thickness Thickness
Weak Large Shallow WLS
Weak Large Mid WLM
Weak Large Deep WLD
Weak Midsize Shallow WMS
Weak Midsize Mid WMM
Weak Midsize Deep WMD
Weak Thin Shallow WTS
Weak Thin Mid WTM
Weak Thin Deep WTD
Midium Large Shallow MLS
Midium Large Mid MLM
Midium Large Deep MLD
Midium Midsize Shallow MMS
Midium Midsize Mid MMM
Midium Midsize Deep MMD
Midium Thin Shallow MTS
Midium Thin Mid MTM
Midium Thin Deep MTD
Strong Large SLX
Strong Medsize SMX
Strong Thin STX
Resit RXX
Fig. 9 Example of liquefaction risk levels for a range of buildings. The LIQUEFACT software produces a number of measures for liquefaction potential along with a qualitative assessment (Very Low to Very High) of the liquefaction risk level for each location. In the Table, when List (Profile) is selected, the displayed values represent the results of liquefaction susceptibility level analysis measured at each location of CPT, SPT or Vs profile. When List is selected, the displayed values are result from the interpolation of the lique- faction severity indicators values that were measured for each CPT, SPT or VS profile
Shepard’s Weighted Average technique. It creates surfaces from measured points, based on either the extent of similarity (inverse distance weighted) or the degree of smoothing (radial basis functions).
Fig. 10 Example of liquefaction risk levels maps in terms a number of indicator measures along with a qualitative assessment, as produced in the LIQUEFACT software
4 Liquefaction risk assessment
LIQUEFACT software provides the users with options at different stages of computation of damage and losses, including: comparison of damage and loss due to liquefaction and Fig. 10 (continued)
due to ground shaking, in considering seismic demand and liquefaction demand for dam- age and loss computation; type of intensity measures for the liquefaction and ground shak- ing fragility functions, number of damage limit states to be considered in the vulnerabil- ity models, and method for the vulnerability analysis (ESP-based or Conventional-based analysis) for liquefaction fragility functions.
4.1 Liquefaction and ground shaking vulnerability analysis
The computation of damage and loss that are caused by liquefaction hazard can be done by defining a set of liquefaction fragility functions. However, it is also possible to simultane- ously compute damage and loss caused by liquefaction hazard, and damage and loss caused by ground shaking (i.e. no consideration of liquefaction) by also defining a set of shaking fragility functions, in addition to the set of liquefaction fragility functions (Fig. 12). The aim of this simultaneous analysis is to allow the users to get a better picture on the impact of liquefaction by comparing the two results (especially in terms of level of uncertainty associated with risk and loss due to the liquefaction hazard).
Regarding the assignment of seismic load indicator (PGA, Sa, Sd) resulting from ground amplification profiles, and liquefaction severity indicators (PGA, Sa, LSN, GD) resulting from liquefaction profiles to the assets (buildings, infrastructures), for the com- putation of the associated damage and loss (see Fig. 13a), the users are offered to choose between: (a) the assigned value of seismic load and liquefaction severity indicators are Fig. 11 Interpolation settings incorporated in the LIQUEFACT software
directly resulted from the closest ground amplification profile and liquefaction profile, respectively, at the location of a given asset or to the closest; and (b) the assigned value of seismic load and liquefaction severity indicators are directly resulted from interpola- tion, at the location of a given asset.
4.2 Computation of damage probability and loss
In the LIQUEFACT software, Liquefaction and Ground Shaking Fragility functions are assumed to take the form of a lognormal cumulative distribution function having a median value and logarithmic standard deviation, or dispersion.
Fig. 12 Alternatives for the computation of damage and loss in the LIQUEFACT software: a computa- tion of damage and loss for liquefaction hazard; b computation of damage and loss for liquefaction and for ground shaking
Fig. 13 Alternatives for the computation of damage and loss in the LIQUEFACT software: a alternatives in considering seismic ground shaking demand and liquefaction demand for a given asset; b ESP-based and Conventional-based methods for considering liquefaction fragility functions
IMds , is the median value of intensity measure at which the building reaches the thresh- old of damage state ds; 𝛽ds , is the standard deviation of the natural logarithm of intensity measure for damage state ds; Φ() is the standard normal cumulative distribution function.
4.2.1 Damage probability
In the LIQUEFACT software, the type of intensity measure for the Engineering Demand Parameter (EDP) will define the procedure for the computation of demand/performance (Bradley et al 2009). For liquefaction vulnerability functions, the users are provided with options in defining intensity measure in terms of Spectral Acceleration (Sa), Peak Ground Acceleration (PGA), Ground Deformation—Differential Settlement (GD), Liquefaction Severity Number (LSN). For ground shaking vulnerability functions, the users can define intensity measures in terms of Spectral Acceleration (Sa), Peak Ground Acceleration (PGA), and Spectral Displacement (Sd) (see Table 3).
The LIQUEFACT software incorporates two methods for the computation of dam- age probability and loss: the Conventional-based method and the ESP-based method. In the conventional procedure, a given building or infrastructure is represented by a single fragility model which is developed as result of a combined structural system-soil profile (Fig. 14a). Regarding the definition of damage thresholds, options are provided in terms of Number of Damage Limit States. The software incorporates the following definitions for the liquefaction and ground shaking fragility models: four Damage Limit States, three Damage Limit States, two Damage Limit States, and one Damage Limit State, as illus- trated in Table 3.
In the ESP-based procedure, which was developed in the framework of the LIQUE- FACT project (Millen et al. 2019a, b; Viana da Fonseca et al. 2018a, b), a given typology (building or infrastructure) is represented by 22 ESP classes (see Fig. 8 and Table 2), and from the resulted ESP-based liquefaction hazard map the software then looks up the ESP- based liquefaction fragility functions that correspond to equivalent soil profile class and building typology and computes the loss. ESP-based liquefaction fragility functions for a given typology is a combination of fragility functions representing: Interstorey Drift of the Superstructure, Residual, Collapse, Foundation Titling. An example of ESP-based Intersto- rey Drift liquefaction fragility functions is shown in Fig. 14b.
4.2.2 Mean loss ratio
Loss Ratio (LR), also called Damage Ratio, is defined as the cost ratio (or loss) to the value or cost of new construction for each portfolio entry and insurance type. LR to a specific building or infrastructure from a given liquefaction severity indicator or ground shaking at a given site is computed by the LIQUEFACT software using the HAZUS (reference) prin- ciples where damage probability is computed in different categories depending on number of Damage Limit States (one, two, three or four Damage Limit States) considered in the selected fragility models. LR in the LIQUEFACT software is used with weights so that it not only reflects damage, but the relative economical loss inflicted. The Mean Loss Ratio (MLR) is defined as the ratio of repair costs (or losses) to the total value, and is extensively
P[ds|IM] = Φ⋅ [
1 𝛽ds ⋅ln
( IM IMds
)]
Table 3 Concept alternatives for configuration of ground shaking and liquefaction fragility functions in terms of number of damage limit states and type of engineering demand parameter (intensity measure) Liquefaction fragility functionsGround shaking fragility functions Number of damage limit states (for conventional fragility functions)Four damage limit states: slight damage, moderate damage, extensive damage and complete damage Three damage limit states: damage limitation, significant damage, and near collapse Two damage limit states: minor damage, and complete damage One damage limit state: collapse Engineering demand parameter (intensity measure)Spectral acceleration (SA)Spectral acceleration (Sa) Peak ground acceleration (PGA)Peak ground acceleration (PGA) Ground deformation—differential settlement (GD)Spectral displacement (Sd) Liquefaction severity number (LSN)
used as a direct representation of the economic losses (for Building, Contents and Business Interruption).
where LRj is the ratio of the cost for damage state j to the total value, and these values are the user changeable. NT is the total number of buildings (of same typology in a given Geo- code) and Nkj denotes the number of buildings of typology k and in damage state j.
4.2.3 Economic and business loss
The LIQUEFACT software includes a module for the computation of Owner and Insur- ance Economic and Business monetary losses. The Owner losses are computed in terms of direct asset loss (due to physical impact), contents loss and business interruption loss. The Insurance losses are also provided in terms of asset insurance loss, contents insurance loss, and business interruption insurance loss.
4.2.4 Results of risk analysis
Results of risk analysis due to liquefaction and ground shaking are computed at both indi- vidual asset (Risk Identification) and Geo-code level. Figure 15 (see also Table 4) and Fig. 16 (see also Table 5) show example applications of Owner Losses computed in the LIQUEFACT software at individual asset level and Geo-code level, respectively. Figure 17 (see also Table 6) and Fig. 18 (see also Table 7) show example applications of Insurance Losses computed in the LIQUEFACT software at individual asset level and Geo-code
MLR=
∑
k
∑
jNjkLRj NT
Fig. 14 Alternatives for the computation of damage and loss in the LIQUEFACT software: a example of liquefaction fragility functions for ESP-based method; b example of liquefaction fragility functions for con- ventional method
level, respectively. Note that the LIQUEFACT software can produce similar type of loss information when considering ground shaking hazard.
5 Liquefaction mitigation assessment
In the LIQUEFACT software, the concept of mitigation analysis includes: a process for selecting an appropriate mitigation measure considering the actual in-site condition, and a process for cost-benefit analysis and socio-economic impact. The concept of selection is processed as Score Rating sequences where the user can develop mitigation framework customized to their case studies. The ground improvement technologies that have been considered in the LIQUEFACT software are the most common in practice for liquefac- tion mitigation. These techniques are categorized into two main groups: (a) measures and techniques applicable in a situation of an existing structure/infrastructures; and (b) meas- ures and techniques applicable in a situation of a free-field condition site (Modoni et al 2019b; Meslem et al. 2019c). It is important to mention that the concept of Level of Appli- cability and Score Rating Evaluation described herein represents one of assumptions and limitations, that are adopted by the LIQUEFACT software, as it is based on experience and expert judgement only, while ground improvement technologies are, indeed, very sensitive to site-condition and environment.
5.1 Selection of ground improvement technologies: level of applicability and score rating evaluation
The technology(s) selection process is based on applicability criteria and score rating considering the most influential factors. The first step in scoring the applicability and eliminate some ground improvement technologies is to define site conditions: if the site or the location of interest is a free-field condition or if there are existing buildings or infrastructures. Other involved factors include soil type, stratigraphy, depth of liquefi- able zone, size of area to be improved, foundation type, constrains, presence any sub- surface obstructions, and environmental compatibility. Table 8 illustrates the list of the factors considered in the system, and they are classified in terms of level of importance Fig. 15 Example of owner loss at individual asset level as produced in the LIQUEFACT software for lique- faction hazard
to the applicability criteria and weighted accordingly. The same Table also illustrates the level of applicability and score rating of ground improvement technologies (for the 10 selected technologies) considering the most influential factors. For each answer to Table 4 Owner loss information at individual asset level, as produced in the LIQUEFACT software Ground liquefaction-related risk
analysis output parameters for owner loss at asset level
Description
Building
Mean loss ratio (building) Is the mean of building loss ratios of a given number of buildings of same Typology located in same geo-code
Monetary values (building) Input Data of monetary value of a given building
Loss (building) Is computed as monetary value (building) multiplied with the mean loss ratio (building)
Contents
Mean loss ratio (contents) Is the mean of content loss ratios of a given number of buildings of same typology located in same geo-code
Monetary values (contents) Input data of monetary value of a given content in a given building Ground liquefaction-related risk
analysis output parameters for owner loss at geo-code level
Description
Mean loss ratio (buildings) Is the mean of loss ratios of all buildings located in a given geo- code
Monetary values (buildings) Input data of total monetary values of all buildings located in a given geo-code
Loss (buildings) Is computed as total monetary value (buildings) multiplied with the mean loss ratio (buildings), in a given geo-code
Mean loss ratio (contents) Is the mean of loss ratios of all contents located in a given Geo- code
Monetary values (contents) Input data of total monetary values of all contents located in a given geo-code
Loss (contents) Is computed as total monetary value (contents) multiplied with the mean loss ratio (contents), in a given geo-code
Mean loss ratio (businesses) Is the mean of loss ratios of all businesses located in a given Geo- code
Monetary values (businesses) Input data of total monetary values of all businesses located in a given geo-code
Loss (businesses) Is computed as total monetary value (businesses) multiplied with the mean loss ratio (businesses), in a given geo-code
Total loss Total loss in a given geo-code
Loss (contents) Is computed as monetary value (contents) multiplied with the mean loss ratio (contents)
Business interruption
Mean loss ratio (business interruption) Is the mean of content loss ratios of a given number of buildings of same typology located in same geo-code
Business revenue Input data of business revenue of a given building
Loss (business interruption) Is computed as business revenue multiplied with the mean loss ratio (business interruption)
a given factor, the weighed score is computed as a value quantified for a given level of applicability multiplied with value quantified for level of importance of the given factor.
For example, for an answer of Free-field to the site condition factor, the weighed score value of 55 is the result of 3 (quantified value for level of applicability in free field condi- tion) multiplied with 18.2% (relative weight quantifying level of importance of the factor site Fig. 16 Example of owner loss at geo-code level, as produced in the LIQUEFACT software for liquefaction hazard
Table 5 Owner Loss information at Geo-code level, as produced in the LIQUEFACT software Ground liquefaction-related risk analysis
output parameters for owner loss at geo-code level
Description
Mean loss ratio (buildings) Is the mean of loss ratios of all buildings located in a given geo-code
Monetary values (buildings) Input data of total monetary values of all buildings located in a given geo-code
Loss (buildings) Is computed as total monetary value (buildings) multiplied with the mean loss ratio (buildings), in a given geo-code Mean loss ratio (contents) Is the mean of loss ratios of all contents located in a given
geo-code
Monetary values (contents) Input data of total monetary values of all contents located in a given geo-code
Loss (contents) Is computed as total monetary value (contents) multiplied with the mean loss ratio (contents), in a given geo-code Mean loss ratio (businesses) Is the mean of loss ratios of all businesses located in a given
geo-code
Monetary values (businesses) Input data of total monetary values of all businesses located in a given geo-code
Loss (businesses) Is computed as total monetary value (businesses) multiplied with the mean loss ratio (businesses), in a given geo-code
Total loss Total loss in a given geo-code
condition). Figure 19 shows illustrative example of results of mitigation analysis in terms of overall applicability score for each of the incorporated ground improvement mitigation tech- niques, as produced in the LIQUEFACT software. The scores of the mitigation technologies are estimated for each considered asset (building or infrastructure) selected for mitigation analysis.
As mentioned earlier, the concept of mitigation assessment adopted in the LIQUEFACT software, is associated with a number of simplified assumption and limitations. Hence, the users are reminded at each stage of the mitigation analysis and results. Hence, a Disclaimer message underlying assumptions and limitations of the software has been added asking the users to Agree or Disagree to conditions of using the Mitigation Analysis System (Fig. 20).
The disclaimer message states that “the mitigation analysis system is provided for guidance only and should not be considered as it is for design decisions. Results obtained from the Mitigation Analysis should be independently cross-checked, and critically reviewed by an experienced engineer with sufficient expertise and having an understanding of the underlying assumptions and limitations of the software”. If the user does not accept the conditions the software will not run the analysis. Even when the users accept the conditions, the software continues reminding them about the underlined assumptions and limitations by displaying the disclaimer message along with the results of mitigation analysis.
5.2 Cost‑benefit analysis
Cost-benefit assessment provides a tool for comparing the costs of a given mitigation strategy to the benefits that can be achieved (Liel and Deierlein 2013). By explicitly quantifying the relationship between mitigation effectiveness and its costs, these assessments facilitate effec- tive decision making for investment in liquefaction risk safety.
CBR= Mitigation Cost(MC) Expected benefit(EB)
Fig. 17 Example of Insurance Loss at individual asset level, as produced in the LIQUEFACT software for liquefaction hazard
Cost-benefit ratios less than unity indicate favourable conditions where the benefits out- weigh the costs. The Expected Benefit (EB) of a given mitigation action over the building’s remaining lifespan is given by:
EB=(
EALI−EALM)
⋅
∑T t=1
(1+r)t
Table 6 Insurance Loss information at individual asset level, as produced in the LIQUEFACT software
Retained loss is the cumulative total of loss that have yet to be paid
Facultative reinsurance is coverage purchased by a primary insurer to cover risks held in the primary insur- er’s book of business
Coinsurance: is the amount, generally expressed as a fixed percentage, an insured must pay against a claim after the deductible is satisfied
CEDED refers to the portion of risk that a primary insurer passes to a reinsurer. It allows the primary insurer to reduce its risk exposure to an insurance policy it has underwritten by passing that risk to another company
Ground liquefaction-related risk analysis out-
put parameters for insurance loss at asset level Description Building
Mean loss ratio (building) Is the mean of building loss ratios of a given number of buildings of same Typology located in same geo-code Insured amount (building) Input data of the insured amount for a given building Retained loss (building) Retained loss of a given building
Facultative loss (building) Facultative loss of a given building Coinsurance loss (building) Coinsurance loss of a given building CEDED loss (building) CECED loss of a given building Contents
Mean loss ratio (contents) Is the mean of content loss ratios of a given number of buildings of same Typology located in same geo-code Insured amount (contents) Input data of the insured amount for contents in a given
building
Retained loss (contents) Contents retained loss of a given building Facultative loss (contents) Contents facultative loss of a given building Coinsurance loss (contents) Contents coinsurance loss of a given building CEDED loss (building) Contents CECED loss of a given building Business interruption
Mean loss ratio (business interruption) Is the mean of business interruption loss ratios of a given number of buildings of same typology located in same geo-code
Insured amount (business interruption) Input data of the insured amount for Business Interruption for a given building
Retained loss (business interruption) Business interruption retained loss of a given building Facultative loss (business interruption) Business interruption facultative loss of a given building Coinsurance loss (business interruption) Business interruption coinsurance loss of a given building CEDED loss (business interruption) Business interruption ceced loss of a given building
where EALI is the Expected Annual Losses before a mitigation strategy is implemented;
EALM is the Expected Annual Losses after a mitigation strategy is implemented; r is con- stant discount rate: is determined from interest rates and adjusted for inflation, and tradi- tionally ranges from 2 to 6%; T: is remaining building life of 50 years. Figure 21 shows how the user can define which ground improvement technologies that will be considered for Cost-Benefit Analysis: (a) by providing mitigation cost by building area (m3), in a local currency, for each technology (if the cost for any given technology is left with zero “0”
value then the technology will not be considered in the mitigation analysis); and (b) by providing their best estimate for the level of efficiency of a given technology in terms of improving ground condition.
Expected Annual Loss (EAL) represents the estimated losses, in terms of an average yearly amount, considering the frequency and severity of possible future earthquake-induced liq- uefaction represented by the seismic and liquefaction hazard at the site of interest. EAL is obtained by combining the Expected Losses E[L|im] associated with the damage and non- damage states of the building/infrastructure asset, integrated overall ground-motion/liquefac- tion intensities 𝜆IM.
Figure 22 shows exemplary results in terms of Cost-Benefit ratio for each of the incorpo- rated ground improvement mitigation techniques, as produced in the LIQUEFACT software.
The costs of the mitigation technologies are estimated for each considered asset selected for mitigation analysis. The software also produces a compiled information summarizing all the mitigation analysis results for each individual asset (Fig. 23).
EAL=
∞
∫
IM=0
E[L|im]⋅𝜆IM
Fig. 18 Example of Insurance Loss at Geo-code level, as produced in the LIQUEFACT software for lique- faction hazard
Table 7 Insurance loss information at Geo-code level, as produced in the LIQUEFACT software
Retained loss is the cumulative total of loss that have yet to be paid
Facultative reinsurance is coverage purchased by a primary insurer to cover risks held in the primary insur- er’s book of business
Coinsurance: is the amount, generally expressed as a fixed percentage, an insured must pay against a claim after the deductible is satisfied
CEDED: refers to the portion of risk that a primary insurer passes to a reinsurer. It allows the primary insurer to reduce its risk exposure to an insurance policy it has underwritten by passing that risk to another company
Ground liquefaction-related risk analysis out- put parameters for insurance loss at geo-code level
Description
Building
Mean loss ratio (buildings) Is the mean of loss ratios of all buildings located in a given geo-code
Insured amount (buildings) Total insured amount for all buildings located in a given geo-code
Retained loss (buildings) Total retained loss considering all buildings located in a given geo-code
Facultative loss (buildings) Total facultative loss considering all buildings located in a given geo-code
Coinsurance loss (buildings) Total coinsurance loss considering all buildings located in a given geo-code
CECED loss (buildings) Total CECED loss considering all buildings located in a given geo-code
Contents
Insured amount (contents) Total insured amount for all contents of buildings located in a given geo-code
Retained loss (contents) Total retained loss considering all contents of buildings located in a given geo-code
Facultative loss (contents) Total facultative loss considering all contents of buildings located in a given geo-code
Coinsurance loss (contents) Total coinsurance loss considering all contents of build- ings located in a given geo-code
CECED loss (contents) Total CECED loss considering all contents of buildings located in a given geo-code
Business interruption
Insured amount (business interruption) Total insured amount for all businesses of buildings located in a given geo-code
Retained loss (business interruption) Total retained loss considering all businesses of buildings located in a given geo-code
Facultative loss (business interruption) Total facultative loss considering all businesses of build- ings located in a given geo-code
Coinsurance loss (business interruption) Total coinsurance loss considering all businesses of build- ings located in a given geo-code
CECED loss (business interruption) Total CECED loss considering all businesses of buildings located in a given geo-code
Total loss Total insurance loss in a given Geo-code
Table 8 Concept for the evaluation of overall score rating for selection of ground improvement mitigation technologies considering the most influential factors of applicability
6 Conclusive remarks
In the framework of the Horizon 2020 LIQUEFACT project, the LIQUEFACT Refer- ence Guide software has been developed as one of the key outputs of the project, incor- porating both data and methodologies collected and elaborated in the project’s various work packages. Specifically, this refers to liquefaction susceptibility level maps, meth- odologies, and results of liquefaction vulnerability analysis for both building typolo- gies and critical infrastructures, liquefaction mitigation measures as well as cost-benefit considerations. The software is targeting a wider range of user groups with different lev- els of technical background as well as requirements (urban planners, facility managers, Fig. 19 Example of mitigation analysis results in terms of overall applicability score for the incorporated ground improvement mitigation techniques, as produced in the LIQUEFACT software for each considered asset (building or infrastructure) selected for mitigation analysis
Fig. 20 Disclaimer message underlying the assumptions and limitations of the LIQUEFACT software
structural and geotechnical engineers, or risk modelers). In doing so, the LIQUEFACT software shall allow the user in making informed assessments on the feasibility and cost-benefit of applying certain liquefaction mitigation techniques for a given earth- quake-induced liquefaction threat. The LIQUEFACT software was designed and devel- oped as an easy-to-use software toolbox, where all the different analysis processes are handled through a robust GUI providing a user-friendly environment for preparing the input information for the LIQUEFACT software and work on the database. The soft- ware also uses a Geographic Information System (GIS) technology, allowing the user to visualize the spatial relationships between various geographic assets or resources for the Fig. 21 Mitigation cost and ben-
efit settings in the LIQUEFACT software
Fig. 22 Example of mitigation analysis results in terms of Cost-Benefit ratio for the incorporated ground improvement mitigation techniques, as produced by the LIQUEFACT software for each considered asset selected for mitigation analysis. Cost-benefit ratios less than unity indicate favourable conditions where the benefits outweigh the costs
specific hazard being modelled, which is considered a crucial function in the planning process.
The development of the software was based on various detailed feedbacks on both the engineering science and practical usefulness of each feature incorporated in the tool.
The development has also been validated during workshops (International Expert Advi- sory Panel review workshops, several workshops with urban planners, facility managers, structural and geotechnical engineers, or risk modelers) and tested at various sites (pub- lished by different project’s partners) during the LIQUEFACT project lifetime. However, it is important to recognize that the software adopts a certain number of assumptions and limitations related to the incorporated data and methodologies. The assumptions and limi- tations of the software are underlined in a Disclaimer message to make sure that the user has a full understanding that this software is provided for guidance only. Design decisions should not, under any condition, be based on the software alone. Results of the LIQUE- FACT software, especially the part related to mitigation analysis, should be independently cross-checked and critically reviewed by an experienced engineer with sufficient expertise.
The LIQUEFACT software will be distributed under a free license, which can ulti- mately result in a larger number of users able to test the software and provide feedback.
This concept will strongly contribute to a rapid development and continuous improvement of the software based on the users’ feedback. The software will be downloadable directly from NORSAR’s website (www.norsa r.no) while the user will be required to register and accept a License Agreement to receive the free license.
Acknowledgements The LIQUEFACT project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 700748.
References
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Fig. 23 Example of compiled information summarizing all the mitigation analysis results for each individ- ual asset, as produced by the LIQUEFACT software
